{"id":"W2917822986","doi":"10.1039/c8nr09816f","title":"Molecularly imprinted nanozymes with faster catalytic activity and better specificity","year":2019,"lang":"en","type":"article","venue":"Nanoscale","topic":"Advanced Nanomaterials in Catalysis","field":"Materials Science","cited_by":87,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; National Institute for Nanotechnology; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Catalysis; Molecular imprinting; Imprinting (psychology); Adsorption; Substrate (aquarium); Chemistry; Nanotechnology; Combinatorial chemistry; Materials science; Selectivity; Organic chemistry; Biochemistry; Biology; Gene","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000237755,0.0005673828,0.0003305149,0.0002114174,0.00007777136,0.000435273,0.0003394199,0.0004688073,0.001388537],"category_scores_gemma":[0.0003955706,0.000259179,0.0003418504,0.0001645872,0.0002352784,0.000501004,0.0001423448,0.0007817034,0.0009247829],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002741547,"about_ca_system_score_gemma":0.0001199332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001435342,"about_ca_topic_score_gemma":0.0004129882,"domain_scores_codex":[0.999775,0.00002312071,0.00001917897,0.00008047702,0.00007374788,0.00002840846],"domain_scores_gemma":[0.9998075,0.0000645965,0.00004692424,0.00002164988,0.00004015335,0.00001906011],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000187491,0.00001456354,0.00005097697,0.00004097763,0.000003916281,0.00001924017,0.000004736142,0.0001577106,0.997022,0.0001289958,0.00005085979,0.002487209],"study_design_scores_gemma":[0.000002234938,0.00003037498,0.0002308512,0.000001514547,0.000003669557,0.00004629622,0.000001829391,0.0008524241,0.9976819,0.00002427981,0.001121952,0.000002682217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8385693,0.006723124,0.1366469,0.0006440327,0.0004607881,0.0001677979,0.0006913097,0.001963187,0.01413363],"genre_scores_gemma":[0.8853303,0.001977519,0.1000914,0.0004089351,0.00005368692,0.000103507,0.0005600292,0.0002079781,0.01126662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001388537,"threshold_uncertainty_score":0.004645169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006842118987347239,"score_gpt":0.2212012769362436,"score_spread":0.2143591579488964,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}